• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.7-13
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• 2022

Radio frequency fingerprinting refers to a methodology that extracts hardware-specific characteristics of a transmitter that are unintentionally embedded in a transmitted waveform. In this paper, we put forward a fingerprinting feature and deep learning structure that can identify the same type of Digital Mobile Radio(DMR) by inputting the in-phase(I) and quadrature(Q). We proposes using the magnitude in polar coordinates of I/Q as RF fingerprinting feature and a modified ResNet-1D structure that can identify them. Experimental results show that our proposed modified ResNet-1D structure can achieve recognition accuracy of 99.5% on 20 DMR.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.111-123
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• 2022

Carbonate green rust (CGR) and sulfate green rust (SGR) commonly occur in nature. In this study, CGR and SGR were synthesized through co-precipitation, and their formation mechanisms and physicochemical properties were investigated. X-ray diffraction (XRD) and Rietveld refinement showed both CGR and SGR with layered double hydroxide structure were successfully synthesized without any secondary phases under each synthetic condition. Refined structural parameters (unit cell) for two green rusts were a (=b) = 3.17 Å and c = 22.52 Å for CGR and a (=b) = 5.50 Å and c = 10.97 Å for SGR with the crystallite size 57.8 nm in diameter from (003) reflection and 40.1 nm from (001) reflections, respectively. Scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) results showed that both CGR and SGR had typical hexagonal plate-like crystal morphologies but their chemical composition is different in the content of C and S. In addition, Fourier transform infrared (FT-IR) spectroscopy analysis revealed that carbonate (CO₃^2-) and sulfate (SO₄^2-) molecules were occupied as interlayer anions of CGR and SGR, respectively. These SEM/EDS and FT-IR results were in good agreement with XRD results. Changes in the solution chemistry (i.e., pH, Eh and residual iron concentrations (Fe(II):Fe(III)) of the mixed solution) were observed as a function of the injection time of hydroxyl ion (OH^-) into the iron solution. Three different stages were observed in the formation of both CGR and SGR; precursor, intermediator, and green rust in the formation of both CGR and SGR. This study provides co-precipitation methods for CGR and SGR in a way of the stable synthesis. In addition, our findings for the formation mechanisms of the two green rusts and their physicochemical properties will provide crucial information with researches and industrials in utilizing green rust.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1433-1443
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• 1993

DCT(Discrete Cosine Transform) / IDCT(Inverse DCT) is widely used in various image compression and decompression systems as well as in DSP(Digital Signal Processing) applications. Since DCT/ IDCT is one of the most complicated part of the compression system, the performance of the system can be greatly enchanced by improving the speed of DCT/IDCT operation. In this thesis, we designed a DCT/IDCT core processor using module generator technique. By utilizing the partial sum and DA(Distributed Arithmetic) techniques, the DCT/ IDCT core processor is designed within small area. It is also designed to perform the IDCT(Inverse DCT) operation with little additional circuitry. The pipeline structure of the core processor enables the high performance, and the high accuracy of the DCT/IDCT operation is obtained by having fewer rounding stages. The proposed design is independent of design rules, and the number of the input bits and the accuracy of the internal calculation coa be easily adjusted due to the module generator technique. The accuracy of the processor satisfies the specifications in CCITT recommendation H, 261.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1727-1737
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• 2018

In this paper, we propose a system to detect spatial structures in land cover maps and to detect time-series spatial structure changes. At first, the proposed system detects patches in a certain area at different times and calculates their measures to analyse spatial structure patterns of the area. Then the system conducts patch mapping among the detected time-series patches and decides 6 types of patch changes such as keeping, creating, disappearing, splitting, merging, and changing in a mixed way. Also, the system stores the patch-based spatial structure patterns of time-series land cover maps in binary form to extract changes. This demonstrated that the proposed change detection system can be used as a basis for planning the reconstruction of the urban spatial structure by measuring the degree of urban sprawl.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.377-382
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• 2004

In the present study, thirteen healthy volunteers performed lumbar extension exercises at 48$^{\circ}$/s, loaded by 40, 50, 60kg(about 44, 55, 66％ of maximum voluntary contraction). During the whole period of exercises, electromyographic(EMG) signal was measured in the erector spinae muscle in order to determine muscle fatigue. Using the wavelet transform, EMG signal was separated by various frequency ranges in the time-frequency domain, and muscle fatigue was analyzed, comparing with the results based on the median frequency(MDF). MDF shifted toward the lower frequency ranges with the muscle fatigue, showing a single characteristic frequency. On the other hand, wavelet transform of EMG signals resulted in increased power amplitude in lower frequency ranges(0-125Hz), and decreased power amplitude in higher frequency ranges(375-468Hz). This study reveals that the muscle fatigue during dynamic movement is explained better by wavelet analysis.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.98-105
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• 2007

In this paper, we propose the method and system which determines the condition for safe and unsafe lane changing. To determine the condition, first, the system sets up the Region of Interest(ROI) on the neighboring lane. Second, a dangerous vehicle is extracted during the line changing. Third, the condition is determined to wm or not by calculating the moving direction, relative distance md relative velocity. To set up the ROI, the only one side lane is detected and the interested region is expanded. Using the coordinate transformation method, the accuracy of the ROI raised. To correctly extract the vehicle on the neighboring lane, the Adaptive Background Update method and Image Segmentation method which uses the feature of the travelling road are used. The object which is extracted by the dangerous vehicle is calculated the relative distance, the relative velocity and the moving average. And then in order to ring, the direction of the vehicle and the condition for safe and unsafe is determined. As minimizes the interested region and uses the feature of the travelling road, the computational quantity is reduced and the accuracy is raised and a stable result on a travelling road images which demands a high speed calculation is showed.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.49-56
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• 2017

This paper proposes a method to improve the left right discrimination performance by eliminating the imaginary target based on the frequency features of the beam pattern for bow array. The beamwidth of the imaginary target is wider than that of the real target. If an azimuth axis is considered as a time axis, the real and the imaginary targets can be assumed as high and low frequencies, respectively. To eliminate the imaginary target which has a low frequency component, we design a cut-off frequency of the High Pass Filter (HPF) using the back-lobe imaginary beamwidth. The real target is estimated by eliminating the imaginary target by applying HPF to the entire power of the beamformer output. Computer simulations show that the proposed method can increase the left right discrimination performance above 8 dB on average.

• The Journal of Engineering Research
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• v.1 no.1
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• pp.23-30
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• 1997

Energy transfer by free convection arises in many engineering applications, such as a hot steam radiator for heating a room, refrigeration coils, electric transformers, heating elements and electronic equipments. Generally unsteady natural convection flow in a horizontal channel with arbitrary wall temperatures and the mathematical and physical basis of convection transport has been considered in general. A physically meaningful exact solution of the problem has been obtained in a closed form by the application of the standard finite sine transform technique. Influences of the governing parameters, the Prandtl number and the Rayleigh number, to bring the flow and heat transfer to final steady states have been discussed separately. For constant values of the arbitray wall temperatures and of the function, determining the average axial velocity, the final steady state is approached in different times respectively for the cases when the Prandtl number Pr>1 and Pr<1. It is also seen that the function, representing the axial temperature gradient, is influenced by none of the governing parameters : but the steady state flow is influenced only by the Rayleigh number. There are, of course, many applications. Free convection strongly influences heat transfer from pipes and transmission lines, as well as from various electronic devices. It is also relevant to the environmental sciences, where it is responsible for oceanic and atmospheric motions, as well as related heat transfer processes.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.959-971
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• 2019

CNN (Convolutional Neural Network) is one representative deep learning algorithm, which can extract high-level spatial and spectral features, and has been applied for hyperspectral image classification. However, one significant drawback behind the application of CNNs in hyperspectral images is the high dimensionality of the data, which increases the training time and processing complexity. To address this problem, several CNN based hyperspectral image classification studies have exploited PCA (Principal Component Analysis) for dimensionality reduction. One limitation to this is that the spectral information of the original image can be lost through PCA. Although it is clear that the use of PCA affects the accuracy and the CNN training time, the impact of PCA for CNN based hyperspectral image classification has been understudied. The purpose of this study is to analyze the quantitative effect of PCA in CNN for hyperspectral image classification. The hyperspectral images were first transformed through PCA and applied into the CNN model by varying the size of the reduced dimensionality. In addition, 2D-CNN and 3D-CNN frameworks were applied to analyze the sensitivity of the PCA with respect to the convolution kernel in the model. Experimental results were evaluated based on classification accuracy, learning time, variance ratio, and training process. The size of the reduced dimensionality was the most efficient when the explained variance ratio recorded 99.7%~99.8%. Since the 3D kernel had higher classification accuracy in the original-CNN than the PCA-CNN in comparison to the 2D-CNN, the results revealed that the dimensionality reduction was relatively less effective in 3D kernel.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.271-281
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• 2005

An electromagnetic type shock wave generator suitable for extracorporeal shock wave therapy has been constructed by employing a solenoid coil. The Property of the shock waves produced by the shock wave generator was evaluated using a needle hydrophone. It was shown that, as the capacitor discharging voltage increased from 8 to 18 kV, the Positive Peak Pressure (P+) of the shock wave increased non-linearly from 10 to 77 Wa. In contrast. the negative peak Pressure (f) varied between -3.2 and -6.8 MPa. had its absolute maximum of -6.9 ma at 14 kV The peak amplitudes P+ measured repeatedly under the same voltage setting varied within $5\;\%$ from mean values and this is very small compared to about $50\;\%$ for electrohydraulic type shock wave generators. It could be observed, from the hydrophone signal recorded over 1 ms. several sequential acoustic impulses representing bubble collapses. namely. acoustic cavitation. induced by the shock wave. A technique based on wavelet transformation was used to accurately measure the time delay between the 1st and 2nd collapse known to be closely related to the shock strength. It was observed that the measured time delay increased almost linearly from 120 to $700\;{\mu}s$ with the shock wave Pressure P+ increasing from 10 to 77 MPa.